Variation principle and the universal metric of dynamic routing

In this paper the variation principles from theoretical physics is considered that would describe the process of routing in computer networks. The total traffic which is currently served on all hops of the route has been chosen as the quantity to minimize. Universal metric function has been found for dynamic routing taking into account the packet loss effect. An attempt to derive the metric of the most popular dynamic routing protocols such as RIP, OSPF, EIGRP from universal metric was made.Comment: 4 pages, 3 figures, 14 equation

Modelling the IEEE 802.11 wireless MAC layer under heterogeneous VoIP traffic to evaluate and dimension QoE

PhDAs computers become more popular in the home and workplace, sharing resources and Internet access locally is a necessity. The simplest method of choice is by deploying a Wireless Local Area Network; they are inexpensive, easy to configure and require minimal infrastructure. The wireless local area network of choice is the IEEE 802.11 standard; IEEE 802.11, however, is now being implemented on larger scales outside of the original scope of usage. The realistic usage spans from small scale home solutions to commercial ‘hot spots,’ providing access within medium size areas such as cafés, and more recently blanket coverage in metropolitan. Due to increasing Internet availability and faster network access, in both wireless and wired, the concept of using such networks for real-time services such as internet telephony is also becoming popular. IEEE 802.11 wireless access is shared with many clients on a single channel and there are three non-overlapping channels available. As more stations communicate on a single channel there is increased contention resulting in longer delays due to the backoff overhead of the IEEE 802.11 protocol and hence loss and delay variation; not desirable for time critical traffic. Simulation of such networks demands super-computing resource, particularly where there are over a dozen clients on a given. Fortunately, the author has access to the UK’s super computers and therefore a clear motivation to develop a state of the art analytical model with the required resources to validate. The goal was to develop an analytical model to deal with realistic IEEE 802.11 deployments and derive results without the need for super computers. A network analytical model is derived to model the characteristics of the IEEE 802.11 protocol from a given scenario, including the number of clients and the traffic load of each. The model is augmented from an existing published saturated case, where each client is assumed to always have traffic to transmit. The nature of the analytical model is to allow stations to have a variable load, which is achieved by modifying the existing models and then to allow stations to operate with different traffic profiles. The different traffic profiles, for each station, is achieved by using the augmented model state machine per station and distributing the probabilities to each station’s state machine accordingly. To address the gap between the analytical models medium access delay and standard network metrics which include the effects of buffering traffic, a queueing model is identified and augmented which transforms the medium access delay into standard network metrics; delay, loss and jitter. A Quality of Experience framework, for both computational and analytical results, is investigated to allow the results to be represented as user perception scores and the acceptable voice call carrying capacity found. To find the acceptable call carrying capacity, the ITU-T G.107 E-Model is employed which can be used to give each client a perception rating in terms of user satisfaction. PAGE 4 OF 162 QUEEN MARY, UNIVERSITY OF LONDON OLIVER SHEPHERD With the use of a novel framework, benchmarking results show that there is potential to maximise the number of calls carried by the network with an acceptable user perception rating. Dimensioning of the network is undertaken, again compared with simulation from the super computers, to highlight the usefulness of the analytical model and framework and provides recommendations for network configurations, particularly for the latest Wireless Multimedia extensions available in IEEE 802.11. Dimensioning shows an overall increase of acceptable capacity of 43%; from 7 to 10 bidirectional calls per Access Point by using a tuned transmission opportunity to allow each station to send 4 packets per transmission. It is found that, although the accuracy of the results from the analytical model is not precise, the model achieves a 1 in 13,000 speed up compared to simulation. Results show that the point of maximum calls comes close to simulation with the analytical model and framework and can be used as a guide to configure the network. Alternatively, for specific capacity figures, the model can be used to home-in on the optimal region for further experiments and therefore achievable with standard computational resource, i.e. desktop machines

Monitoring multicast traffic in heterogeneous networks

Estágio realizado no INESC - Porto e orientado pelo Prof. Doutor Ricardo MorlaTese de mestrado integrado. Engenharia Electrotécnica e de Computadores - Major Telecomunicações. Faculdade de Engenharia. Universidade do Porto. 200

QoS in LEO satellite networks with multipacket reception

Dissertação apresentada para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores, pela Universidade Nova de Lisboa, Faculdade de Ciências e TecnologiaLow Earth Orbit (LEO) satellite networks can improve terrestrial wireless networks to allow global broadband services for Mobile Terminals (MT), regardless of the users' location. In this context, hybrid telecommunication systems combining satellites with Long Term Evolution (LTE) networks, like the LightSquared technology, are intended to provide ubiquitous high-speed services. This dissertation analyses the performance of a random access protocol that uses Hybrid Network-assisted Diversity Multiple Access (H-NDMA), for a LEO satellite system network, named by Satellite Random NDMA (SR-NDMA). The protocol also considers a Single Carrier-Frequency Domain Equalization (SC-FDE) scheme for the uplink transmission and a Multipacket Reception (MPR) receiver. In this scenario, the transmission of data packets between MTs and the Base Station (BS) is made through random access and schedule access slots, organized into super-frames with the duration of a Round Trip Time (RTT). A SR-NDMA simulator is implemented to measure the system performance in matters of throughput, energy consumption, system delay and also the protocol capacity to meet Quality of Service (QoS) requirements. A set of simulations tests were made with a random Poisson process tra c generation to validate the analytical model. The capacity to ful l the QoS requirements of a real-time tra c class was also tested.FCT/MEC: MPSat - PTDC/EEA-TEL/099074/2008, OPPORTUNISTIC CR - PTDC/EEA-TEL/115981/2009, Femtocells - PTDC/EEA-TEL/120666/2010 e ADIN - PTDC/EEI-TEL/2990/201

A traffic engineering system for DiffServ/MPLS networks

This thesis presents an approach to traffic engineering that uses DiffServ and MPLS technologies to provide QoS guarantees over an IP network. The specific problem described here is how best to route traffic within the network such that the demands can be carried with the requisite QoS while balancing the load on the network. A traffic engineering algorithm that determines QoS guaranteed label-switched paths (LSPs) between specified ingress-egress pairs is proposed and a system that uses such an algorithm is outlined. The algorithm generates a solution for the QoS routing problem of finding a path with a number of constraints (delay, jitter, loss) while trying to make best of resource utilisation. The key component of the system is a central resource manager responsible for monitoring and managing resources within the network and making all decisions to route traffic according to QoS requirements. The algorithm for determining QoS-constrained routes is based on the notion of effective bandwidth and cost functions for load balancing. The network simulation of the proposed system is presented here and simulation results are discussed

Delay analysis of mixed fronthaul and backhaul traffic under strict priority queueing discipline in a 5G packet transport network

Virtualization of the base station for the purpose of centralization is being actively studied and researched as an implementation option for 5G mobile networks. Proposed as Cloud radio access network, the technology is expected to facilitate easier operation and maintenance than regular radio access networks. However, the base stations traffic has stringent delay requirements. In this paper, we explore the possibility of multiplexing fronthaul traffic and traditional backhaul traffic as it traverses over the metropolitan network while keeping the average fronthaul queueing delay and jitter under control. We analyze and simulate the cases of a single fronthaul flow and multiple fronthaul flows arriving at the packet switch assuming strict priority for the fronthaul queue. We propose a fronthaul frame aggregation strategy to improve the packet transmission efficiency while keeping the average fronthaul queueing delay and jitter constant regardless of the percentage of fronthaul traffic. While the criteria for aggregation is different for the 2 cases, we show that the optimal number of basic frames to aggregate is between 3-10 frames assuming the Common Public Radio Interface protocol.The authors would like to acknowledge the support of projects TIGRE5-CM (grant no. S2013/ICE-2919) and H2020 EU-funded 5G-Crosshaul Project (grant no. 671598) to the development of this work

Performance enhancement of large scale networks with heterogeneous traffic.

Finally, these findings are applied towards improving the performance of the Differentiated Services architecture by developing a new Refined Assured Forwarding framework where heterogeneous traffic flows share the same aggregate class. The new framework requires minimal modification to the existing Diffserv routers. The efficiency of the new architecture in enhancing the performance of Diffserv is demonstrated by simulation results under different traffic scenarios.This dissertation builds on the notion that segregating traffic with disparate characteristics into separate channels generally results in a better performance. Through a quantitative analysis, it precisely defines the number of classes and the allocation of traffic into these classes that will lead to optimal performance from a latency standpoint. Additionally, it weakens the most generally used assumption of exponential or geometric distribution of traffic service time in the integration versus segregation studies to date by including self-similarity in network traffic.The dissertation also develops a pricing model based on resource usage in a system with segregated channels. Based on analytical results, this dissertation proposes a scheme whereby a service provider can develop compensatory and fair prices for customers with varying QoS requirements under a wide variety of ambient traffic scenarios.This dissertation provides novel techniques for improving the Quality of Service by enhancing the performance of queue management in large scale packet switched networks with a high volume of traffic. Networks combine traffic from multiple sources which have disparate characteristics. Multiplexing such heterogeneous traffic usually results in adverse effects on the overall performance of the network

RouteNet-Fermi: Network Modeling with Graph Neural Networks

Network models are an essential block of modern networks. For example, they are widely used in network planning and optimization. However, as networks increase in scale and complexity, some models present limitations, such as the assumption of Markovian traffic in queuing theory models, or the high computational cost of network simulators. Recent advances in machine learning, such as Graph Neural Networks (GNN), are enabling a new generation of network models that are data-driven and can learn complex non-linear behaviors. In this paper, we present RouteNet-Fermi, a custom GNN model that shares the same goals as Queuing Theory, while being considerably more accurate in the presence of realistic traffic models. The proposed model predicts accurately the delay, jitter, and packet loss of a network. We have tested RouteNet-Fermi in networks of increasing size (up to 300 nodes), including samples with mixed traffic profiles -- e.g., with complex non-Markovian models -- and arbitrary routing and queue scheduling configurations. Our experimental results show that RouteNet-Fermi achieves similar accuracy as computationally-expensive packet-level simulators and scales accurately to larger networks. Our model produces delay estimates with a mean relative error of 6.24% when applied to a test dataset of 1,000 samples, including network topologies one order of magnitude larger than those seen during training. Finally, we have also evaluated RouteNet-Fermi with measurements from a physical testbed and packet traces from a real-life network.Comment: This paper has been accepted for publication at IEEE/ACM Transactions on Networking 2023 (DOI: 10.1109/TNET.2023.3269983). \copyright 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other use